AI Deployment Strategist, Enterprise

Scale AI•San Francisco, CA

8h•$192,800 - $241,000•Hybrid

About The Position

Scale's Enterprise Applications business is growing faster than ever in the quest to develop reliable AI systems for the world's most important decisions. As an AI Deployment Strategist you will be right at the center of it, helping our largest customers build, launch, and scale groundbreaking GenAI solutions that redefine their industries. You will take full ownership of our deployment success, turning bold ideas into real impact and ensuring every engagement delivers exceptional results. In this role, you will work directly with data, engineering, business and AI leaders at some of the world's top Enterprises. You will guide projects from the first conversation through delivery, expansion, and measurable business outcomes. Within Scale, you will collaborate closely with Machine Learning, Engineering, Product, and Finance teams to streamline execution, improve processes, and shape our approach to enterprise delivery. This is a fast-moving, high-impact role that blends customer strategy, operations, product strategy and execution. You will lead the team that serves as the voice of the customer and ensure their flawless execution of customer projects.

Requirements

Experience from one of three places we've hired strong Deployment Strategists out of: (1) operators at companies that deploy enterprise AI or data products (Palantir DS or FDE-style roles, and the equivalents elsewhere), (2) Strategy consultants from BCG, McKinsey, or Bain who've moved into tech because they want to own outcomes, or (3) technical PMs or engineers who got pulled into the business and customer side and never looked back. These are profiles that have worked well, we are always open to other profiles that fit our role requirements.
5-8 years in high-growth, high-ambiguity environments.
A technical or quantitative background (CS, engineering, economics, statistics, STEM) helps.
Low ego, high hunger. You take direct feedback well, name your own weaknesses honestly, and run at hard problems.
A diagnose-before-you-solve instinct. Hypothesis-driven. You ask two layers of questions before reaching for a framework.
Zero jargon. You can turn a technical concept into business impact a CFO would act on, and a delivery plan an engineer would execute against.
Technical credibility. No engineering degree required. You are curious enough to push back on engineering leads when the architecture or the accuracy story doesn't hold up.
Commercial instinct. You think in business levers. You articulate ROI without prompting and spot upsell logic the AE missed.
Grit. You stick through tough periods. We are wary of project-hoppers.
Willingness to travel 30-50 percent, which can include international trips depending on the account.

Nice To Haves

Hands-on experience with enterprise AI or data infrastructure products
Deeper industry knowledge in healthcare, financial services, or consumer

Responsibilities

The customer outcome: You are the on-the-ground DRI. Renewals and expansion happen because the deployment worked, and the deployment working is your job.
Repeatable delivery: On time, at quality, with deployment standards you define and enforce. When internal or external teams are not moving fast enough, you push them.
The next workstream: You see where AI unlocks new business value inside an account before the customer does. You frame the case and bring it to life with our AE and product teams.
Unsticking what's stuck: When something is blocked, you go fix it. With Engineering, Product, Finance, Ops, whoever it takes.
Feedback that shapes the product: You bring what's working and what isn't back to product and leadership in a way they can act on.